As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

Types for Google Cloud Datalabeling v1beta1 API¶

class google.cloud.datalabeling_v1beta1.types.AnnotatedDataset(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

AnnotatedDataset is a set holding annotations for data in a Dataset. Each labeling task will generate an AnnotatedDataset under the Dataset that the task is requested for.

name¶

Output only. AnnotatedDataset resource name in format of: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}

Type: str

display_name¶

Output only. The display name of the AnnotatedDataset. It is specified in HumanAnnotationConfig when user starts a labeling task. Maximum of 64 characters.

Type: str

description¶

Output only. The description of the AnnotatedDataset. It is specified in HumanAnnotationConfig when user starts a labeling task. Maximum of 10000 characters.

Type: str

annotation_source¶

Output only. Source of the annotation.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSource

annotation_type¶

Output only. Type of the annotation. It is specified when starting labeling task.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationType

example_count¶

Output only. Number of examples in the annotated dataset.

Type: int

completed_example_count¶

Output only. Number of examples that have annotation in the annotated dataset.

Type: int

label_stats¶

Output only. Per label statistics.

Type: google.cloud.datalabeling_v1beta1.types.LabelStats

create_time¶

Output only. Time the AnnotatedDataset was created.

Type: google.protobuf.timestamp_pb2.Timestamp

metadata¶

Output only. Additional information about AnnotatedDataset.

Type: google.cloud.datalabeling_v1beta1.types.AnnotatedDatasetMetadata

blocking_resources¶

Output only. The names of any related resources that are blocking changes to the annotated dataset.

Type: MutableSequence[str]

class google.cloud.datalabeling_v1beta1.types.AnnotatedDatasetMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Metadata on AnnotatedDataset.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

image_classification_config¶

Configuration for image classification task.

This field is a member of oneof annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.ImageClassificationConfig

bounding_poly_config¶

Configuration for image bounding box and bounding poly task.

This field is a member of oneof annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.BoundingPolyConfig

polyline_config¶

Configuration for image polyline task.

This field is a member of oneof annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.PolylineConfig

segmentation_config¶

Configuration for image segmentation task.

This field is a member of oneof annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.SegmentationConfig

video_classification_config¶

Configuration for video classification task.

This field is a member of oneof annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.VideoClassificationConfig

object_detection_config¶

Configuration for video object detection task.

This field is a member of oneof annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.ObjectDetectionConfig

object_tracking_config¶

Configuration for video object tracking task.

This field is a member of oneof annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.ObjectTrackingConfig

event_config¶

Configuration for video event labeling task.

This field is a member of oneof annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.EventConfig

text_classification_config¶

Configuration for text classification task.

This field is a member of oneof annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.TextClassificationConfig

text_entity_extraction_config¶

Configuration for text entity extraction task.

This field is a member of oneof annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.TextEntityExtractionConfig

human_annotation_config¶

HumanAnnotationConfig used when requesting the human labeling task for this AnnotatedDataset.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.Annotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Annotation for Example. Each example may have one or more annotations. For example in image classification problem, each image might have one or more labels. We call labels binded with this image an Annotation.

name¶

Output only. Unique name of this annotation, format is:

projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/{annotated_dataset}/examples/{example_id}/annotations/{annotation_id}

Type: str

annotation_source¶

Output only. The source of the annotation.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSource

annotation_value¶

Output only. This is the actual annotation value, e.g classification, bounding box values are stored here.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationValue

annotation_metadata¶

Output only. Annotation metadata, including information like votes for labels.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationMetadata

annotation_sentiment¶

Output only. Sentiment for this annotation.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSentiment

class google.cloud.datalabeling_v1beta1.types.AnnotationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Additional information associated with the annotation.

operator_metadata¶

Metadata related to human labeling.

Type: google.cloud.datalabeling_v1beta1.types.OperatorMetadata

class google.cloud.datalabeling_v1beta1.types.AnnotationSentiment(value)[source]¶

Bases: proto.enums.Enum

Values:

ANNOTATION_SENTIMENT_UNSPECIFIED (0):: No description available.
NEGATIVE (1):: This annotation describes negatively about the data.
POSITIVE (2):: This label describes positively about the data.

class google.cloud.datalabeling_v1beta1.types.AnnotationSource(value)[source]¶

Bases: proto.enums.Enum

Specifies where the annotation comes from (whether it was provided by a human labeler or a different source).

Values:

ANNOTATION_SOURCE_UNSPECIFIED (0):: No description available.
OPERATOR (3):: Answer is provided by a human contributor.

class google.cloud.datalabeling_v1beta1.types.AnnotationSpec(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Container of information related to one possible annotation that can be used in a labeling task. For example, an image classification task where images are labeled as dog or cat must reference an AnnotationSpec for dog and an AnnotationSpec for cat.

display_name¶

Required. The display name of the AnnotationSpec. Maximum of 64 characters.

Type: str

description¶

Optional. User-provided description of the annotation specification. The description can be up to 10,000 characters long.

Type: str

class google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

An AnnotationSpecSet is a collection of label definitions. For example, in image classification tasks, you define a set of possible labels for images as an AnnotationSpecSet. An AnnotationSpecSet is immutable upon creation.

name¶

Output only. The AnnotationSpecSet resource name in the following format:

“projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}”.

Type: str

display_name¶

Required. The display name for AnnotationSpecSet that you define when you create it. Maximum of 64 characters.

Type: str

description¶

Optional. User-provided description of the annotation specification set. The description can be up to 10,000 characters long.

Type: str

annotation_specs¶

Required. The array of AnnotationSpecs that you define when you create the AnnotationSpecSet. These are the possible labels for the labeling task.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.AnnotationSpec]

blocking_resources¶

Output only. The names of any related resources that are blocking changes to the annotation spec set.

Type: MutableSequence[str]

class google.cloud.datalabeling_v1beta1.types.AnnotationType(value)[source]¶

Bases: proto.enums.Enum

Values:

ANNOTATION_TYPE_UNSPECIFIED (0):: No description available.
IMAGE_CLASSIFICATION_ANNOTATION (1):: Classification annotations in an image. Allowed for continuous evaluation.
IMAGE_BOUNDING_BOX_ANNOTATION (2):: Bounding box annotations in an image. A form of image object detection. Allowed for continuous evaluation.
IMAGE_ORIENTED_BOUNDING_BOX_ANNOTATION (13):: Oriented bounding box. The box does not have to be parallel to horizontal line.
IMAGE_BOUNDING_POLY_ANNOTATION (10):: Bounding poly annotations in an image.
IMAGE_POLYLINE_ANNOTATION (11):: Polyline annotations in an image.
IMAGE_SEGMENTATION_ANNOTATION (12):: Segmentation annotations in an image.
VIDEO_SHOTS_CLASSIFICATION_ANNOTATION (3):: Classification annotations in video shots.
VIDEO_OBJECT_TRACKING_ANNOTATION (4):: Video object tracking annotation.
VIDEO_OBJECT_DETECTION_ANNOTATION (5):: Video object detection annotation.
VIDEO_EVENT_ANNOTATION (6):: Video event annotation.
TEXT_CLASSIFICATION_ANNOTATION (8):: Classification for text. Allowed for continuous evaluation.
TEXT_ENTITY_EXTRACTION_ANNOTATION (9):: Entity extraction for text.
GENERAL_CLASSIFICATION_ANNOTATION (14):: General classification. Allowed for continuous evaluation.

class google.cloud.datalabeling_v1beta1.types.AnnotationValue(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Annotation value for an example.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

image_classification_annotation¶

Annotation value for image classification case.

This field is a member of oneof value_type.

Type: google.cloud.datalabeling_v1beta1.types.ImageClassificationAnnotation

image_bounding_poly_annotation¶

Annotation value for image bounding box, oriented bounding box and polygon cases.

This field is a member of oneof value_type.

Type: google.cloud.datalabeling_v1beta1.types.ImageBoundingPolyAnnotation

image_polyline_annotation¶

Annotation value for image polyline cases. Polyline here is different from BoundingPoly. It is formed by line segments connected to each other but not closed form(Bounding Poly). The line segments can cross each other.

This field is a member of oneof value_type.

Type: google.cloud.datalabeling_v1beta1.types.ImagePolylineAnnotation

image_segmentation_annotation¶

Annotation value for image segmentation.

This field is a member of oneof value_type.

Type: google.cloud.datalabeling_v1beta1.types.ImageSegmentationAnnotation

text_classification_annotation¶

Annotation value for text classification case.

This field is a member of oneof value_type.

Type: google.cloud.datalabeling_v1beta1.types.TextClassificationAnnotation

text_entity_extraction_annotation¶

Annotation value for text entity extraction case.

This field is a member of oneof value_type.

Type: google.cloud.datalabeling_v1beta1.types.TextEntityExtractionAnnotation

video_classification_annotation¶

Annotation value for video classification case.

This field is a member of oneof value_type.

Type: google.cloud.datalabeling_v1beta1.types.VideoClassificationAnnotation

video_object_tracking_annotation¶

Annotation value for video object detection and tracking case.

This field is a member of oneof value_type.

Type: google.cloud.datalabeling_v1beta1.types.VideoObjectTrackingAnnotation

video_event_annotation¶

Annotation value for video event case.

This field is a member of oneof value_type.

Type: google.cloud.datalabeling_v1beta1.types.VideoEventAnnotation

class google.cloud.datalabeling_v1beta1.types.Attempt(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Records a failed evaluation job run.

attempt_time¶

Type: google.protobuf.timestamp_pb2.Timestamp

partial_failures¶

Details of errors that occurred.

Type: MutableSequence[google.rpc.status_pb2.Status]

class google.cloud.datalabeling_v1beta1.types.BigQuerySource(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

The BigQuery location for input data. If used in an [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob], this is where the service saves the prediction input and output sampled from the model version.

input_uri¶

Required. BigQuery URI to a table, up to 2,000 characters long. If you specify the URI of a table that does not exist, Data Labeling Service creates a table at the URI with the correct schema when you create your [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob]. If you specify the URI of a table that already exists, it must have the correct schema.

Provide the table URI in the following format:

“bq://{your_project_id}/{your_dataset_name}/{your_table_name}”

Learn more.

Type: str

class google.cloud.datalabeling_v1beta1.types.BoundingBoxEvaluationOptions(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Options regarding evaluation between bounding boxes.

iou_threshold¶

Minimum [intersection-over-union

(IOU)](/vision/automl/object-detection/docs/evaluate#intersection-over-union) required for 2 bounding boxes to be considered a match. This must be a number between 0 and 1.

Type: float

class google.cloud.datalabeling_v1beta1.types.BoundingPoly(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A bounding polygon in the image.

vertices¶

The bounding polygon vertices.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.Vertex]

class google.cloud.datalabeling_v1beta1.types.BoundingPolyConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for image bounding poly (and bounding box) human labeling task.

annotation_spec_set¶

Required. Annotation spec set resource name.

Type: str

instruction_message¶

Optional. Instruction message showed on contributors UI.

Type: str

class google.cloud.datalabeling_v1beta1.types.ClassificationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Metadata for classification annotations.

is_multi_label¶

Whether the classification task is multi-label or not.

Type: bool

class google.cloud.datalabeling_v1beta1.types.ClassificationMetrics(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Metrics calculated for a classification model.

pr_curve¶

Precision-recall curve based on ground truth labels, predicted labels, and scores for the predicted labels.

Type: google.cloud.datalabeling_v1beta1.types.PrCurve

confusion_matrix¶

Confusion matrix of predicted labels vs. ground truth labels.

Type: google.cloud.datalabeling_v1beta1.types.ConfusionMatrix

class google.cloud.datalabeling_v1beta1.types.ConfusionMatrix(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Confusion matrix of the model running the classification. Only applicable when the metrics entry aggregates multiple labels. Not applicable when the entry is for a single label.

row¶

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.ConfusionMatrix.Row]

class ConfusionMatrixEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

annotation_spec¶

The annotation spec of a predicted label.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

item_count¶

Number of items predicted to have this label. (The ground truth label for these items is the Row.annotationSpec of this entry’s parent.)

Type: int

class Row(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A row in the confusion matrix. Each entry in this row has the same ground truth label.

annotation_spec¶

The annotation spec of the ground truth label for this row.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

entries¶

A list of the confusion matrix entries. One entry for each possible predicted label.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.ConfusionMatrix.ConfusionMatrixEntry]

class google.cloud.datalabeling_v1beta1.types.CreateAnnotationSpecSetRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for CreateAnnotationSpecSet.

parent¶

Required. AnnotationSpecSet resource parent, format: projects/{project_id}

Type: str

annotation_spec_set¶

Required. Annotation spec set to create. Annotation specs must be included. Only one annotation spec will be accepted for annotation specs with same display_name.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet

class google.cloud.datalabeling_v1beta1.types.CreateDatasetRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for CreateDataset.

parent¶

Required. Dataset resource parent, format: projects/{project_id}

Type: str

dataset¶

Required. The dataset to be created.

Type: google.cloud.datalabeling_v1beta1.types.Dataset

class google.cloud.datalabeling_v1beta1.types.CreateEvaluationJobRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for CreateEvaluationJob.

parent¶

Required. Evaluation job resource parent. Format: “projects/{project_id}”.

Type: str

job¶

Required. The evaluation job to create.

Type: google.cloud.datalabeling_v1beta1.types.EvaluationJob

class google.cloud.datalabeling_v1beta1.types.CreateInstructionMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Metadata of a CreateInstruction operation.

instruction¶

The name of the created Instruction. projects/{project_id}/instructions/{instruction_id}

Type: str

partial_failures¶

Partial failures encountered. E.g. single files that couldn’t be read. Status details field will contain standard GCP error details.

Type: MutableSequence[google.rpc.status_pb2.Status]

create_time¶

Timestamp when create instruction request was created.

Type: google.protobuf.timestamp_pb2.Timestamp

class google.cloud.datalabeling_v1beta1.types.CreateInstructionRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for CreateInstruction.

parent¶

Required. Instruction resource parent, format: projects/{project_id}

Type: str

instruction¶

Required. Instruction of how to perform the labeling task.

Type: google.cloud.datalabeling_v1beta1.types.Instruction

class google.cloud.datalabeling_v1beta1.types.CsvInstruction(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Deprecated: this instruction format is not supported any more. Instruction from a CSV file.

gcs_file_uri¶

CSV file for the instruction. Only gcs path is allowed.

Type: str

class google.cloud.datalabeling_v1beta1.types.DataItem(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

DataItem is a piece of data, without annotation. For example, an image.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

image_payload¶

The image payload, a container of the image bytes/uri.

This field is a member of oneof payload.

Type: google.cloud.datalabeling_v1beta1.types.ImagePayload

text_payload¶

The text payload, a container of text content.

This field is a member of oneof payload.

Type: google.cloud.datalabeling_v1beta1.types.TextPayload

video_payload¶

The video payload, a container of the video uri.

This field is a member of oneof payload.

Type: google.cloud.datalabeling_v1beta1.types.VideoPayload

name¶

Output only. Name of the data item, in format of: projects/{project_id}/datasets/{dataset_id}/dataItems/{data_item_id}

Type: str

class google.cloud.datalabeling_v1beta1.types.DataType(value)[source]¶

Bases: proto.enums.Enum

Values:

DATA_TYPE_UNSPECIFIED (0):: No description available.
IMAGE (1):: Allowed for continuous evaluation.
VIDEO (2):: No description available.
TEXT (4):: Allowed for continuous evaluation.
GENERAL_DATA (6):: Allowed for continuous evaluation.

class google.cloud.datalabeling_v1beta1.types.Dataset(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Dataset is the resource to hold your data. You can request multiple labeling tasks for a dataset while each one will generate an AnnotatedDataset.

name¶

Output only. Dataset resource name, format is: projects/{project_id}/datasets/{dataset_id}

Type: str

display_name¶

Required. The display name of the dataset. Maximum of 64 characters.

Type: str

description¶

Optional. User-provided description of the annotation specification set. The description can be up to 10000 characters long.

Type: str

create_time¶

Output only. Time the dataset is created.

Type: google.protobuf.timestamp_pb2.Timestamp

input_configs¶

Output only. This is populated with the original input configs where ImportData is called. It is available only after the clients import data to this dataset.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.InputConfig]

blocking_resources¶

Output only. The names of any related resources that are blocking changes to the dataset.

Type: MutableSequence[str]

data_item_count¶

Output only. The number of data items in the dataset.

Type: int

class google.cloud.datalabeling_v1beta1.types.DeleteAnnotatedDatasetRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for DeleteAnnotatedDataset.

name¶

Required. Name of the annotated dataset to delete, format: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}

Type: str

class google.cloud.datalabeling_v1beta1.types.DeleteAnnotationSpecSetRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for DeleteAnnotationSpecSet.

name¶

Required. AnnotationSpec resource name, format: projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}.

Type: str

class google.cloud.datalabeling_v1beta1.types.DeleteDatasetRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for DeleteDataset.

name¶

Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

Type: str

class google.cloud.datalabeling_v1beta1.types.DeleteEvaluationJobRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message DeleteEvaluationJob.

name¶

Required. Name of the evaluation job that is going to be deleted. Format:

“projects/{project_id}/evaluationJobs/{evaluation_job_id}”.

Type: str

class google.cloud.datalabeling_v1beta1.types.DeleteInstructionRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for DeleteInstruction.

name¶

Required. Instruction resource name, format: projects/{project_id}/instructions/{instruction_id}

Type: str

class google.cloud.datalabeling_v1beta1.types.Evaluation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Describes an evaluation between a machine learning model’s predictions and ground truth labels. Created when an [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob] runs successfully.

name¶

Output only. Resource name of an evaluation. The name has the following format:

“projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}’

Type: str

config¶

Output only. Options used in the evaluation job that created this evaluation.

Type: google.cloud.datalabeling_v1beta1.types.EvaluationConfig

evaluation_job_run_time¶

Output only. Timestamp for when the evaluation job that created this evaluation ran.

Type: google.protobuf.timestamp_pb2.Timestamp

create_time¶

Output only. Timestamp for when this evaluation was created.

Type: google.protobuf.timestamp_pb2.Timestamp

evaluation_metrics¶

Output only. Metrics comparing predictions to ground truth labels.

Type: google.cloud.datalabeling_v1beta1.types.EvaluationMetrics

annotation_type¶

Output only. Type of task that the model version being evaluated performs, as defined in the

[evaluationJobConfig.inputConfig.annotationType][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config] field of the evaluation job that created this evaluation.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationType

evaluated_item_count¶

Output only. The number of items in the ground truth dataset that were used for this evaluation. Only populated when the evaulation is for certain AnnotationTypes.

Type: int

class google.cloud.datalabeling_v1beta1.types.EvaluationConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Configuration details used for calculating evaluation metrics and creating an [Evaluation][google.cloud.datalabeling.v1beta1.Evaluation].

bounding_box_evaluation_options¶

Only specify this field if the related model performs image object detection (IMAGE_BOUNDING_BOX_ANNOTATION). Describes how to evaluate bounding boxes.

This field is a member of oneof vertical_option.

Type: google.cloud.datalabeling_v1beta1.types.BoundingBoxEvaluationOptions

class google.cloud.datalabeling_v1beta1.types.EvaluationJob(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Defines an evaluation job that runs periodically to generate [Evaluations][google.cloud.datalabeling.v1beta1.Evaluation]. Creating an evaluation job is the starting point for using continuous evaluation.

name¶

Output only. After you create a job, Data Labeling Service assigns a name to the job with the following format:

“projects/{project_id}/evaluationJobs/{evaluation_job_id}”.

Type: str

description¶

Required. Description of the job. The description can be up to 25,000 characters long.

Type: str

state¶

Output only. Describes the current state of the job.

Type: google.cloud.datalabeling_v1beta1.types.EvaluationJob.State

schedule¶

Required. Describes the interval at which the job runs. This interval must be at least 1 day, and it is rounded to the nearest day. For example, if you specify a 50-hour interval, the job runs every 2 days.

You can provide the schedule in crontab format or in an English-like format.

Regardless of what you specify, the job will run at 10:00 AM UTC. Only the interval from this schedule is used, not the specific time of day.

Type: str

model_version¶

Required. The AI Platform Prediction model version to be evaluated. Prediction input and output is sampled from this model version. When creating an evaluation job, specify the model version in the following format:

“projects/{project_id}/models/{model_name}/versions/{version_name}”

There can only be one evaluation job per model version.

Type: str

evaluation_job_config¶

Required. Configuration details for the evaluation job.

Type: google.cloud.datalabeling_v1beta1.types.EvaluationJobConfig

annotation_spec_set¶

Required. Name of the [AnnotationSpecSet][google.cloud.datalabeling.v1beta1.AnnotationSpecSet] describing all the labels that your machine learning model outputs. You must create this resource before you create an evaluation job and provide its name in the following format:

“projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}”.

Type: str

label_missing_ground_truth¶

Required. Whether you want Data Labeling Service to provide ground truth labels for prediction input. If you want the service to assign human labelers to annotate your data, set this to true. If you want to provide your own ground truth labels in the evaluation job’s BigQuery table, set this to false.

Type: bool

attempts¶

Output only. Every time the evaluation job runs and an error occurs, the failed attempt is appended to this array.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.Attempt]

create_time¶

Output only. Timestamp of when this evaluation job was created.

Type: google.protobuf.timestamp_pb2.Timestamp

class State(value)[source]¶

Bases: proto.enums.Enum

State of the job.

Values:

STATE_UNSPECIFIED (0):

No description available.

SCHEDULED (1):

The job is scheduled to run at the [configured interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. You can [pause][google.cloud.datalabeling.v1beta1.DataLabelingService.PauseEvaluationJob] or [delete][google.cloud.datalabeling.v1beta1.DataLabelingService.DeleteEvaluationJob] the job.

When the job is in this state, it samples prediction input and output from your model version into your BigQuery table as predictions occur.

RUNNING (2):

The job is currently running. When the job runs, Data Labeling Service does several things:

If you have configured your job to use Data Labeling Service for ground truth labeling, the service creates a [Dataset][google.cloud.datalabeling.v1beta1.Dataset] and a labeling task for all data sampled since the last time the job ran. Human labelers provide ground truth labels for your data. Human labeling may take hours, or even days, depending on how much data has been sampled. The job remains in the RUNNING state during this time, and it can even be running multiple times in parallel if it gets triggered again (for example 24 hours later) before the earlier run has completed. When human labelers have finished labeling the data, the next step occurs. If you have configured your job to provide your own ground truth labels, Data Labeling Service still creates a [Dataset][google.cloud.datalabeling.v1beta1.Dataset] for newly sampled data, but it expects that you have already added ground truth labels to the BigQuery table by this time. The next step occurs immediately.
Data Labeling Service creates an [Evaluation][google.cloud.datalabeling.v1beta1.Evaluation] by comparing your model version’s predictions with the ground truth labels.

If the job remains in this state for a long time, it continues to sample prediction data into your BigQuery table and will run again at the next interval, even if it causes the job to run multiple times in parallel.

PAUSED (3):

The job is not sampling prediction input and output into your BigQuery table and it will not run according to its schedule. You can [resume][google.cloud.datalabeling.v1beta1.DataLabelingService.ResumeEvaluationJob] the job.

STOPPED (4):

The job has this state right before it is deleted.

class google.cloud.datalabeling_v1beta1.types.EvaluationJobAlertConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Provides details for how an evaluation job sends email alerts based on the results of a run.

email¶

Required. An email address to send alerts to.

Type: str

min_acceptable_mean_average_precision¶

Required. A number between 0 and 1 that describes a minimum mean average precision threshold. When the evaluation job runs, if it calculates that your model version’s predictions from the recent interval have [meanAveragePrecision][google.cloud.datalabeling.v1beta1.PrCurve.mean_average_precision] below this threshold, then it sends an alert to your specified email.

Type: float

class google.cloud.datalabeling_v1beta1.types.EvaluationJobConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Configures specific details of how a continuous evaluation job works. Provide this configuration when you create an EvaluationJob.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

image_classification_config¶

Specify this field if your model version performs image classification or general classification.

annotationSpecSet in this configuration must match [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set]. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].

This field is a member of oneof human_annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.ImageClassificationConfig

bounding_poly_config¶

Specify this field if your model version performs image object detection (bounding box detection).

annotationSpecSet in this configuration must match [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set].

This field is a member of oneof human_annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.BoundingPolyConfig

text_classification_config¶

Specify this field if your model version performs text classification.

annotationSpecSet in this configuration must match [EvaluationJob.annotationSpecSet][google.cloud.datalabeling.v1beta1.EvaluationJob.annotation_spec_set]. allowMultiLabel in this configuration must match classificationMetadata.isMultiLabel in [input_config][google.cloud.datalabeling.v1beta1.EvaluationJobConfig.input_config].

This field is a member of oneof human_annotation_request_config.

Type: google.cloud.datalabeling_v1beta1.types.TextClassificationConfig

input_config¶

Rquired. Details for the sampled prediction input. Within this configuration, there are requirements for several fields:

dataType must be one of IMAGE, TEXT, or GENERAL_DATA.
annotationType must be one of IMAGE_CLASSIFICATION_ANNOTATION, TEXT_CLASSIFICATION_ANNOTATION, GENERAL_CLASSIFICATION_ANNOTATION, or IMAGE_BOUNDING_BOX_ANNOTATION (image object detection).
If your machine learning model performs classification, you must specify classificationMetadata.isMultiLabel.
You must specify bigquerySource (not gcsSource).

Type: google.cloud.datalabeling_v1beta1.types.InputConfig

evaluation_config¶

Required. Details for calculating evaluation metrics and creating [Evaulations][google.cloud.datalabeling.v1beta1.Evaluation]. If your model version performs image object detection, you must specify the boundingBoxEvaluationOptions field within this configuration. Otherwise, provide an empty object for this configuration.

Type: google.cloud.datalabeling_v1beta1.types.EvaluationConfig

human_annotation_config¶

Optional. Details for human annotation of your data. If you set [labelMissingGroundTruth][google.cloud.datalabeling.v1beta1.EvaluationJob.label_missing_ground_truth] to true for this evaluation job, then you must specify this field. If you plan to provide your own ground truth labels, then omit this field.

Note that you must create an [Instruction][google.cloud.datalabeling.v1beta1.Instruction] resource before you can specify this field. Provide the name of the instruction resource in the instruction field within this configuration.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

bigquery_import_keys¶

Required. Prediction keys that tell Data Labeling Service where to find the data for evaluation in your BigQuery table. When the service samples prediction input and output from your model version and saves it to BigQuery, the data gets stored as JSON strings in the BigQuery table. These keys tell Data Labeling Service how to parse the JSON.

You can provide the following entries in this field:

data_json_key: the data key for prediction input. You must provide either this key or reference_json_key.
reference_json_key: the data reference key for prediction input. You must provide either this key or data_json_key.
label_json_key: the label key for prediction output. Required.
label_score_json_key: the score key for prediction output. Required.
bounding_box_json_key: the bounding box key for prediction output. Required if your model version perform image object detection.

Learn how to configure prediction keys.

Type: MutableMapping[str, str]

example_count¶

Required. The maximum number of predictions to sample and save to BigQuery during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. This limit overrides example_sample_percentage: even if the service has not sampled enough predictions to fulfill example_sample_perecentage during an interval, it stops sampling predictions when it meets this limit.

Type: int

example_sample_percentage¶

Required. Fraction of predictions to sample and save to BigQuery during each [evaluation interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. For example, 0.1 means 10% of predictions served by your model version get saved to BigQuery.

Type: float

evaluation_job_alert_config¶

Optional. Configuration details for evaluation job alerts. Specify this field if you want to receive email alerts if the evaluation job finds that your predictions have low mean average precision during a run.

Type: google.cloud.datalabeling_v1beta1.types.EvaluationJobAlertConfig

class BigqueryImportKeysEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)¶: Bases: proto.message.Message

class google.cloud.datalabeling_v1beta1.types.EvaluationMetrics(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

classification_metrics¶

This field is a member of oneof metrics.

Type: google.cloud.datalabeling_v1beta1.types.ClassificationMetrics

object_detection_metrics¶

This field is a member of oneof metrics.

Type: google.cloud.datalabeling_v1beta1.types.ObjectDetectionMetrics

class google.cloud.datalabeling_v1beta1.types.EventConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for video event human labeling task.

annotation_spec_sets¶

Required. The list of annotation spec set resource name. Similar to video classification, we support selecting event from multiple AnnotationSpecSet at the same time.

Type: MutableSequence[str]

class google.cloud.datalabeling_v1beta1.types.Example(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

An Example is a piece of data and its annotation. For example, an image with label “house”.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

image_payload¶

The image payload, a container of the image bytes/uri.

This field is a member of oneof payload.

Type: google.cloud.datalabeling_v1beta1.types.ImagePayload

text_payload¶

The text payload, a container of the text content.

This field is a member of oneof payload.

Type: google.cloud.datalabeling_v1beta1.types.TextPayload

video_payload¶

The video payload, a container of the video uri.

This field is a member of oneof payload.

Type: google.cloud.datalabeling_v1beta1.types.VideoPayload

name¶

Output only. Name of the example, in format of: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}/examples/{example_id}

Type: str

annotations¶

Output only. Annotations for the piece of data in Example. One piece of data can have multiple annotations.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.Annotation]

class google.cloud.datalabeling_v1beta1.types.ExportDataOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Metadata of an ExportData operation.

dataset¶

Output only. The name of dataset to be exported. “projects//datasets/”.

Type: str

partial_failures¶

Output only. Partial failures encountered. E.g. single files that couldn’t be read. Status details field will contain standard GCP error details.

Type: MutableSequence[google.rpc.status_pb2.Status]

create_time¶

Output only. Timestamp when export dataset request was created.

Type: google.protobuf.timestamp_pb2.Timestamp

class google.cloud.datalabeling_v1beta1.types.ExportDataOperationResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Response used for ExportDataset longrunning operation.

dataset¶

Ouptut only. The name of dataset. “projects//datasets/”.

Type: str

total_count¶

Output only. Total number of examples requested to export

Type: int

export_count¶

Output only. Number of examples exported successfully.

Type: int

label_stats¶

Output only. Statistic infos of labels in the exported dataset.

Type: google.cloud.datalabeling_v1beta1.types.LabelStats

output_config¶

Output only. output_config in the ExportData request.

Type: google.cloud.datalabeling_v1beta1.types.OutputConfig

class google.cloud.datalabeling_v1beta1.types.ExportDataRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for ExportData API.

name¶

Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

Type: str

annotated_dataset¶

Required. Annotated dataset resource name. DataItem in Dataset and their annotations in specified annotated dataset will be exported. It’s in format of projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}

Type: str

filter¶

Optional. Filter is not supported at this moment.

Type: str

output_config¶

Required. Specify the output destination.

Type: google.cloud.datalabeling_v1beta1.types.OutputConfig

user_email_address¶

Email of the user who started the export task and should be notified by email. If empty no notification will be sent.

Type: str

class google.cloud.datalabeling_v1beta1.types.GcsDestination(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Export destination of the data.Only gcs path is allowed in output_uri.

output_uri¶

Required. The output uri of destination file.

Type: str

mime_type¶

Required. The format of the gcs destination. Only “text/csv” and “application/json” are supported.

Type: str

class google.cloud.datalabeling_v1beta1.types.GcsFolderDestination(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Export folder destination of the data.

output_folder_uri¶

Required. Cloud Storage directory to export data to.

Type: str

class google.cloud.datalabeling_v1beta1.types.GcsSource(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Source of the Cloud Storage file to be imported.

input_uri¶

Required. The input URI of source file. This must be a Cloud Storage path (gs://...).

Type: str

mime_type¶

Required. The format of the source file. Only “text/csv” is supported.

Type: str

class google.cloud.datalabeling_v1beta1.types.GetAnnotatedDatasetRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for GetAnnotatedDataset.

name¶

Required. Name of the annotated dataset to get, format: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}

Type: str

class google.cloud.datalabeling_v1beta1.types.GetAnnotationSpecSetRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for GetAnnotationSpecSet.

name¶

Required. AnnotationSpecSet resource name, format: projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}

Type: str

class google.cloud.datalabeling_v1beta1.types.GetDataItemRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for GetDataItem.

name¶

Required. The name of the data item to get, format: projects/{project_id}/datasets/{dataset_id}/dataItems/{data_item_id}

Type: str

class google.cloud.datalabeling_v1beta1.types.GetDatasetRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for GetDataSet.

name¶

Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

Type: str

class google.cloud.datalabeling_v1beta1.types.GetEvaluationJobRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for GetEvaluationJob.

name¶

Required. Name of the evaluation job. Format:

“projects/{project_id}/evaluationJobs/{evaluation_job_id}”.

Type: str

class google.cloud.datalabeling_v1beta1.types.GetEvaluationRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for GetEvaluation.

name¶

Required. Name of the evaluation. Format:

“projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}’

Type: str

class google.cloud.datalabeling_v1beta1.types.GetExampleRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for GetExample

name¶

Required. Name of example, format: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}/examples/{example_id}

Type: str

filter¶

Optional. An expression for filtering Examples. Filter by annotation_spec.display_name is supported. Format “annotation_spec.display_name = {display_name}”.

Type: str

class google.cloud.datalabeling_v1beta1.types.GetInstructionRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for GetInstruction.

name¶

Required. Instruction resource name, format: projects/{project_id}/instructions/{instruction_id}

Type: str

class google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Configuration for how human labeling task should be done.

instruction¶

Required. Instruction resource name.

Type: str

annotated_dataset_display_name¶

Required. A human-readable name for AnnotatedDataset defined by users. Maximum of 64 characters .

Type: str

annotated_dataset_description¶

Optional. A human-readable description for AnnotatedDataset. The description can be up to 10000 characters long.

Type: str

label_group¶

Optional. A human-readable label used to logically group labeling tasks. This string must match the regular expression [a-zA-Z\\d_-]{0,128}.

Type: str

language_code¶

Optional. The Language of this question, as a BCP-47. Default value is en-US. Only need to set this when task is language related. For example, French text classification.

Type: str

replica_count¶

Optional. Replication of questions. Each question will be sent to up to this number of contributors to label. Aggregated answers will be returned. Default is set to 1. For image related labeling, valid values are 1, 3, 5.

Type: int

question_duration¶

Optional. Maximum duration for contributors to answer a question. Maximum is 3600 seconds. Default is 3600 seconds.

Type: google.protobuf.duration_pb2.Duration

contributor_emails¶

Optional. If you want your own labeling contributors to manage and work on this labeling request, you can set these contributors here. We will give them access to the question types in crowdcompute. Note that these emails must be registered in crowdcompute worker UI:

https://crowd-compute.appspot.com/

Type: MutableSequence[str]

user_email_address¶

Email of the user who started the labeling task and should be notified by email. If empty no notification will be sent.

Type: str

class google.cloud.datalabeling_v1beta1.types.ImageBoundingPolyAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Image bounding poly annotation. It represents a polygon including bounding box in the image.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

bounding_poly¶

This field is a member of oneof bounded_area.

Type: google.cloud.datalabeling_v1beta1.types.BoundingPoly

normalized_bounding_poly¶

This field is a member of oneof bounded_area.

Type: google.cloud.datalabeling_v1beta1.types.NormalizedBoundingPoly

annotation_spec¶

Label of object in this bounding polygon.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

class google.cloud.datalabeling_v1beta1.types.ImageClassificationAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Image classification annotation definition.

annotation_spec¶

Label of image.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

class google.cloud.datalabeling_v1beta1.types.ImageClassificationConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for image classification human labeling task.

annotation_spec_set¶

Required. Annotation spec set resource name.

Type: str

allow_multi_label¶

Optional. If allow_multi_label is true, contributors are able to choose multiple labels for one image.

Type: bool

answer_aggregation_type¶

Optional. The type of how to aggregate answers.

Type: google.cloud.datalabeling_v1beta1.types.StringAggregationType

class google.cloud.datalabeling_v1beta1.types.ImagePayload(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Container of information about an image.

mime_type¶

Image format.

Type: str

image_thumbnail¶

A byte string of a thumbnail image.

Type: bytes

image_uri¶

Image uri from the user bucket.

Type: str

signed_uri¶

Signed uri of the image file in the service bucket.

Type: str

class google.cloud.datalabeling_v1beta1.types.ImagePolylineAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A polyline for the image annotation.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

polyline¶

This field is a member of oneof poly.

Type: google.cloud.datalabeling_v1beta1.types.Polyline

normalized_polyline¶

This field is a member of oneof poly.

Type: google.cloud.datalabeling_v1beta1.types.NormalizedPolyline

annotation_spec¶

Label of this polyline.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

class google.cloud.datalabeling_v1beta1.types.ImageSegmentationAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Image segmentation annotation.

annotation_colors¶

The mapping between rgb color and annotation spec. The key is the rgb color represented in format of rgb(0, 0, 0). The value is the AnnotationSpec.

Type: MutableMapping[str, google.cloud.datalabeling_v1beta1.types.AnnotationSpec]

mime_type¶

Image format.

Type: str

image_bytes¶

A byte string of a full image’s color map.

Type: bytes

class AnnotationColorsEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)¶: Bases: proto.message.Message

class google.cloud.datalabeling_v1beta1.types.ImportDataOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Metadata of an ImportData operation.

dataset¶

Output only. The name of imported dataset. “projects//datasets/”.

Type: str

partial_failures¶

Output only. Partial failures encountered. E.g. single files that couldn’t be read. Status details field will contain standard GCP error details.

Type: MutableSequence[google.rpc.status_pb2.Status]

create_time¶

Output only. Timestamp when import dataset request was created.

Type: google.protobuf.timestamp_pb2.Timestamp

class google.cloud.datalabeling_v1beta1.types.ImportDataOperationResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Response used for ImportData longrunning operation.

dataset¶

Ouptut only. The name of imported dataset.

Type: str

total_count¶

Output only. Total number of examples requested to import

Type: int

import_count¶

Output only. Number of examples imported successfully.

Type: int

class google.cloud.datalabeling_v1beta1.types.ImportDataRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for ImportData API.

name¶

Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

Type: str

input_config¶

Required. Specify the input source of the data.

Type: google.cloud.datalabeling_v1beta1.types.InputConfig

user_email_address¶

Email of the user who started the import task and should be notified by email. If empty no notification will be sent.

Type: str

class google.cloud.datalabeling_v1beta1.types.InputConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

The configuration of input data, including data type, location, etc.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

text_metadata¶

Required for text import, as language code must be specified.

This field is a member of oneof data_type_metadata.

Type: google.cloud.datalabeling_v1beta1.types.TextMetadata

gcs_source¶

Source located in Cloud Storage.

This field is a member of oneof source.

Type: google.cloud.datalabeling_v1beta1.types.GcsSource

bigquery_source¶

Source located in BigQuery. You must specify this field if you are using this InputConfig in an [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob].

This field is a member of oneof source.

Type: google.cloud.datalabeling_v1beta1.types.BigQuerySource

data_type¶

Required. Data type must be specifed when user tries to import data.

Type: google.cloud.datalabeling_v1beta1.types.DataType

annotation_type¶

Optional. The type of annotation to be performed on this data. You must specify this field if you are using this InputConfig in an [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob].

Type: google.cloud.datalabeling_v1beta1.types.AnnotationType

classification_metadata¶

Optional. Metadata about annotations for the input. You must specify this field if you are using this InputConfig in an [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob] for a model version that performs classification.

Type: google.cloud.datalabeling_v1beta1.types.ClassificationMetadata

class google.cloud.datalabeling_v1beta1.types.Instruction(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Instruction of how to perform the labeling task for human operators. Currently only PDF instruction is supported.

name¶

Output only. Instruction resource name, format: projects/{project_id}/instructions/{instruction_id}

Type: str

display_name¶

Required. The display name of the instruction. Maximum of 64 characters.

Type: str

description¶

Optional. User-provided description of the instruction. The description can be up to 10000 characters long.

Type: str

create_time¶

Output only. Creation time of instruction.

Type: google.protobuf.timestamp_pb2.Timestamp

update_time¶

Output only. Last update time of instruction.

Type: google.protobuf.timestamp_pb2.Timestamp

data_type¶

Required. The data type of this instruction.

Type: google.cloud.datalabeling_v1beta1.types.DataType

csv_instruction¶

Deprecated: this instruction format is not supported any more. Instruction from a CSV file, such as for classification task. The CSV file should have exact two columns, in the following format:

The first column is labeled data, such as an image reference, text.
The second column is comma separated labels associated with data.

Type: google.cloud.datalabeling_v1beta1.types.CsvInstruction

pdf_instruction¶

Instruction from a PDF document. The PDF should be in a Cloud Storage bucket.

Type: google.cloud.datalabeling_v1beta1.types.PdfInstruction

blocking_resources¶

Output only. The names of any related resources that are blocking changes to the instruction.

Type: MutableSequence[str]

class google.cloud.datalabeling_v1beta1.types.LabelImageBoundingBoxOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of a LabelImageBoundingBox operation metadata.

basic_config¶

Basic human annotation config used in labeling request.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelImageBoundingPolyOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of LabelImageBoundingPoly operation metadata.

basic_config¶

Basic human annotation config used in labeling request.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelImageClassificationOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Metadata of a LabelImageClassification operation.

basic_config¶

Basic human annotation config used in labeling request.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelImageOrientedBoundingBoxOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of a LabelImageOrientedBoundingBox operation metadata.

basic_config¶

Basic human annotation config.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelImagePolylineOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of LabelImagePolyline operation metadata.

basic_config¶

Basic human annotation config used in labeling request.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelImageRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for starting an image labeling task.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

image_classification_config¶

Configuration for image classification task. One of image_classification_config, bounding_poly_config, polyline_config and segmentation_config are required.

This field is a member of oneof request_config.

Type: google.cloud.datalabeling_v1beta1.types.ImageClassificationConfig

bounding_poly_config¶

Configuration for bounding box and bounding poly task. One of image_classification_config, bounding_poly_config, polyline_config and segmentation_config are required.

This field is a member of oneof request_config.

Type: google.cloud.datalabeling_v1beta1.types.BoundingPolyConfig

polyline_config¶

Configuration for polyline task. One of image_classification_config, bounding_poly_config, polyline_config and segmentation_config are required.

This field is a member of oneof request_config.

Type: google.cloud.datalabeling_v1beta1.types.PolylineConfig

segmentation_config¶

Configuration for segmentation task. One of image_classification_config, bounding_poly_config, polyline_config and segmentation_config are required.

This field is a member of oneof request_config.

Type: google.cloud.datalabeling_v1beta1.types.SegmentationConfig

parent¶

Required. Name of the dataset to request labeling task, format: projects/{project_id}/datasets/{dataset_id}

Type: str

basic_config¶

Required. Basic human annotation config.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

feature¶

Required. The type of image labeling task.

Type: google.cloud.datalabeling_v1beta1.types.LabelImageRequest.Feature

class Feature(value)[source]¶

Bases: proto.enums.Enum

Image labeling task feature.

Values:

FEATURE_UNSPECIFIED (0):: No description available.
CLASSIFICATION (1):: Label whole image with one or more of labels.
BOUNDING_BOX (2):: Label image with bounding boxes for labels.
ORIENTED_BOUNDING_BOX (6):: Label oriented bounding box. The box does not have to be parallel to horizontal line.
BOUNDING_POLY (3):: Label images with bounding poly. A bounding poly is a plane figure that is bounded by a finite chain of straight line segments closing in a loop.
POLYLINE (4):: Label images with polyline. Polyline is formed by connected line segments which are not in closed form.
SEGMENTATION (5):: Label images with segmentation. Segmentation is different from bounding poly since it is more fine-grained, pixel level annotation.

class google.cloud.datalabeling_v1beta1.types.LabelImageSegmentationOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of a LabelImageSegmentation operation metadata.

basic_config¶

Basic human annotation config.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Metadata of a labeling operation, such as LabelImage or LabelVideo. Next tag: 20

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

image_classification_details¶

Details of label image classification operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelImageClassificationOperationMetadata

image_bounding_box_details¶

Details of label image bounding box operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelImageBoundingBoxOperationMetadata

image_bounding_poly_details¶

Details of label image bounding poly operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelImageBoundingPolyOperationMetadata

image_oriented_bounding_box_details¶

Details of label image oriented bounding box operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelImageOrientedBoundingBoxOperationMetadata

image_polyline_details¶

Details of label image polyline operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelImagePolylineOperationMetadata

image_segmentation_details¶

Details of label image segmentation operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelImageSegmentationOperationMetadata

video_classification_details¶

Details of label video classification operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelVideoClassificationOperationMetadata

video_object_detection_details¶

Details of label video object detection operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelVideoObjectDetectionOperationMetadata

video_object_tracking_details¶

Details of label video object tracking operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelVideoObjectTrackingOperationMetadata

video_event_details¶

Details of label video event operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelVideoEventOperationMetadata

text_classification_details¶

Details of label text classification operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelTextClassificationOperationMetadata

text_entity_extraction_details¶

Details of label text entity extraction operation.

This field is a member of oneof details.

Type: google.cloud.datalabeling_v1beta1.types.LabelTextEntityExtractionOperationMetadata

progress_percent¶

Output only. Progress of label operation. Range: [0, 100].

Type: int

partial_failures¶

Output only. Partial failures encountered. E.g. single files that couldn’t be read. Status details field will contain standard GCP error details.

Type: MutableSequence[google.rpc.status_pb2.Status]

create_time¶

Output only. Timestamp when labeling request was created.

Type: google.protobuf.timestamp_pb2.Timestamp

class google.cloud.datalabeling_v1beta1.types.LabelStats(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Statistics about annotation specs.

example_count¶

Map of each annotation spec’s example count. Key is the annotation spec name and value is the number of examples for that annotation spec. If the annotated dataset does not have annotation spec, the map will return a pair where the key is empty string and value is the total number of annotations.

Type: MutableMapping[str, int]

class ExampleCountEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)¶: Bases: proto.message.Message

class google.cloud.datalabeling_v1beta1.types.LabelTextClassificationOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of a LabelTextClassification operation metadata.

basic_config¶

Basic human annotation config used in labeling request.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelTextEntityExtractionOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of a LabelTextEntityExtraction operation metadata.

basic_config¶

Basic human annotation config used in labeling request.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelTextRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for LabelText.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

text_classification_config¶

Configuration for text classification task. One of text_classification_config and text_entity_extraction_config is required.

This field is a member of oneof request_config.

Type: google.cloud.datalabeling_v1beta1.types.TextClassificationConfig

text_entity_extraction_config¶

Configuration for entity extraction task. One of text_classification_config and text_entity_extraction_config is required.

This field is a member of oneof request_config.

Type: google.cloud.datalabeling_v1beta1.types.TextEntityExtractionConfig

parent¶

Required. Name of the data set to request labeling task, format: projects/{project_id}/datasets/{dataset_id}

Type: str

basic_config¶

Required. Basic human annotation config.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

feature¶

Required. The type of text labeling task.

Type: google.cloud.datalabeling_v1beta1.types.LabelTextRequest.Feature

class Feature(value)[source]¶

Bases: proto.enums.Enum

Text labeling task feature.

Values:

FEATURE_UNSPECIFIED (0):: No description available.
TEXT_CLASSIFICATION (1):: Label text content to one of more labels.
TEXT_ENTITY_EXTRACTION (2):: Label entities and their span in text.

class google.cloud.datalabeling_v1beta1.types.LabelVideoClassificationOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of a LabelVideoClassification operation metadata.

basic_config¶

Basic human annotation config used in labeling request.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelVideoEventOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of a LabelVideoEvent operation metadata.

basic_config¶

Basic human annotation config used in labeling request.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelVideoObjectDetectionOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of a LabelVideoObjectDetection operation metadata.

basic_config¶

Basic human annotation config used in labeling request.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelVideoObjectTrackingOperationMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Details of a LabelVideoObjectTracking operation metadata.

basic_config¶

Basic human annotation config used in labeling request.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

class google.cloud.datalabeling_v1beta1.types.LabelVideoRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for LabelVideo.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

video_classification_config¶

Configuration for video classification task. One of video_classification_config, object_detection_config, object_tracking_config and event_config is required.

This field is a member of oneof request_config.

Type: google.cloud.datalabeling_v1beta1.types.VideoClassificationConfig

object_detection_config¶

Configuration for video object detection task. One of video_classification_config, object_detection_config, object_tracking_config and event_config is required.

This field is a member of oneof request_config.

Type: google.cloud.datalabeling_v1beta1.types.ObjectDetectionConfig

object_tracking_config¶

Configuration for video object tracking task. One of video_classification_config, object_detection_config, object_tracking_config and event_config is required.

This field is a member of oneof request_config.

Type: google.cloud.datalabeling_v1beta1.types.ObjectTrackingConfig

event_config¶

Configuration for video event task. One of video_classification_config, object_detection_config, object_tracking_config and event_config is required.

This field is a member of oneof request_config.

Type: google.cloud.datalabeling_v1beta1.types.EventConfig

parent¶

Required. Name of the dataset to request labeling task, format: projects/{project_id}/datasets/{dataset_id}

Type: str

basic_config¶

Required. Basic human annotation config.

Type: google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig

feature¶

Required. The type of video labeling task.

Type: google.cloud.datalabeling_v1beta1.types.LabelVideoRequest.Feature

class Feature(value)[source]¶

Bases: proto.enums.Enum

Video labeling task feature.

Values:

FEATURE_UNSPECIFIED (0):: No description available.
CLASSIFICATION (1):: Label whole video or video segment with one or more labels.
OBJECT_DETECTION (2):: Label objects with bounding box on image frames extracted from the video.
OBJECT_TRACKING (3):: Label and track objects in video.
EVENT (4):: Label the range of video for the specified events.

class google.cloud.datalabeling_v1beta1.types.ListAnnotatedDatasetsRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for ListAnnotatedDatasets.

parent¶

Required. Name of the dataset to list annotated datasets, format: projects/{project_id}/datasets/{dataset_id}

Type: str

filter¶

Optional. Filter is not supported at this moment.

Type: str

page_size¶

Optional. Requested page size. Server may return fewer results than requested. Default value is 100.

Type: int

page_token¶

Optional. A token identifying a page of results for the server to return. Typically obtained by [ListAnnotatedDatasetsResponse.next_page_token][google.cloud.datalabeling.v1beta1.ListAnnotatedDatasetsResponse.next_page_token] of the previous [DataLabelingService.ListAnnotatedDatasets] call. Return first page if empty.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListAnnotatedDatasetsResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Results of listing annotated datasets for a dataset.

annotated_datasets¶

The list of annotated datasets to return.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.AnnotatedDataset]

next_page_token¶

A token to retrieve next page of results.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListAnnotationSpecSetsRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for ListAnnotationSpecSets.

parent¶

Required. Parent of AnnotationSpecSet resource, format: projects/{project_id}

Type: str

filter¶

Optional. Filter is not supported at this moment.

Type: str

page_size¶

Optional. Requested page size. Server may return fewer results than requested. Default value is 100.

Type: int

page_token¶

Optional. A token identifying a page of results for the server to return. Typically obtained by [ListAnnotationSpecSetsResponse.next_page_token][google.cloud.datalabeling.v1beta1.ListAnnotationSpecSetsResponse.next_page_token] of the previous [DataLabelingService.ListAnnotationSpecSets] call. Return first page if empty.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListAnnotationSpecSetsResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Results of listing annotation spec set under a project.

annotation_spec_sets¶

The list of annotation spec sets.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet]

next_page_token¶

A token to retrieve next page of results.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListDataItemsRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for ListDataItems.

parent¶

Required. Name of the dataset to list data items, format: projects/{project_id}/datasets/{dataset_id}

Type: str

filter¶

Optional. Filter is not supported at this moment.

Type: str

page_size¶

Optional. Requested page size. Server may return fewer results than requested. Default value is 100.

Type: int

page_token¶

Optional. A token identifying a page of results for the server to return. Typically obtained by [ListDataItemsResponse.next_page_token][google.cloud.datalabeling.v1beta1.ListDataItemsResponse.next_page_token] of the previous [DataLabelingService.ListDataItems] call. Return first page if empty.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListDataItemsResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Results of listing data items in a dataset.

data_items¶

The list of data items to return.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.DataItem]

next_page_token¶

A token to retrieve next page of results.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListDatasetsRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for ListDataset.

parent¶

Required. Dataset resource parent, format: projects/{project_id}

Type: str

filter¶

Optional. Filter on dataset is not supported at this moment.

Type: str

page_size¶

Optional. Requested page size. Server may return fewer results than requested. Default value is 100.

Type: int

page_token¶

Optional. A token identifying a page of results for the server to return. Typically obtained by [ListDatasetsResponse.next_page_token][google.cloud.datalabeling.v1beta1.ListDatasetsResponse.next_page_token] of the previous [DataLabelingService.ListDatasets] call. Returns the first page if empty.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListDatasetsResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Results of listing datasets within a project.

datasets¶

The list of datasets to return.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.Dataset]

next_page_token¶

A token to retrieve next page of results.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListEvaluationJobsRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for ListEvaluationJobs.

parent¶

Required. Evaluation job resource parent. Format: “projects/{project_id}”.

Type: str

filter¶

Optional. You can filter the jobs to list by model_id (also known as model_name, as described in [EvaluationJob.modelVersion][google.cloud.datalabeling.v1beta1.EvaluationJob.model_version]) or by evaluation job state (as described in [EvaluationJob.state][google.cloud.datalabeling.v1beta1.EvaluationJob.state]). To filter by both criteria, use the AND operator or the OR operator. For example, you can use the following string for your filter: “evaluationjob.model_id = {model_name} AND evaluationjob.state = {evaluation_job_state}”.

Type: str

page_size¶

Optional. Requested page size. Server may return fewer results than requested. Default value is 100.

Type: int

page_token¶

Optional. A token identifying a page of results for the server to return. Typically obtained by the [nextPageToken][google.cloud.datalabeling.v1beta1.ListEvaluationJobsResponse.next_page_token] in the response to the previous request. The request returns the first page if this is empty.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListEvaluationJobsResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Results for listing evaluation jobs.

evaluation_jobs¶

The list of evaluation jobs to return.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.EvaluationJob]

next_page_token¶

A token to retrieve next page of results.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListExamplesRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for ListExamples.

parent¶

Required. Example resource parent.

Type: str

filter¶

Optional. An expression for filtering Examples. For annotated datasets that have annotation spec set, filter by annotation_spec.display_name is supported. Format “annotation_spec.display_name = {display_name}”.

Type: str

page_size¶

Optional. Requested page size. Server may return fewer results than requested. Default value is 100.

Type: int

page_token¶

Optional. A token identifying a page of results for the server to return. Typically obtained by [ListExamplesResponse.next_page_token][google.cloud.datalabeling.v1beta1.ListExamplesResponse.next_page_token] of the previous [DataLabelingService.ListExamples] call. Return first page if empty.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListExamplesResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Results of listing Examples in and annotated dataset.

examples¶

The list of examples to return.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.Example]

next_page_token¶

A token to retrieve next page of results.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListInstructionsRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for ListInstructions.

parent¶

Required. Instruction resource parent, format: projects/{project_id}

Type: str

filter¶

Optional. Filter is not supported at this moment.

Type: str

page_size¶

Optional. Requested page size. Server may return fewer results than requested. Default value is 100.

Type: int

page_token¶

Optional. A token identifying a page of results for the server to return. Typically obtained by [ListInstructionsResponse.next_page_token][google.cloud.datalabeling.v1beta1.ListInstructionsResponse.next_page_token] of the previous [DataLabelingService.ListInstructions] call. Return first page if empty.

Type: str

class google.cloud.datalabeling_v1beta1.types.ListInstructionsResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Results of listing instructions under a project.

instructions¶

The list of Instructions to return.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.Instruction]

next_page_token¶

A token to retrieve next page of results.

Type: str

class google.cloud.datalabeling_v1beta1.types.NormalizedBoundingPoly(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Normalized bounding polygon.

normalized_vertices¶

The bounding polygon normalized vertices.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.NormalizedVertex]

class google.cloud.datalabeling_v1beta1.types.NormalizedPolyline(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Normalized polyline.

normalized_vertices¶

The normalized polyline vertices.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.NormalizedVertex]

class google.cloud.datalabeling_v1beta1.types.NormalizedVertex(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1.

x¶

X coordinate.

Type: float

y¶

Y coordinate.

Type: float

class google.cloud.datalabeling_v1beta1.types.ObjectDetectionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for video object detection human labeling task. Object detection will be conducted on the images extracted from the video, and those objects will be labeled with bounding boxes. User need to specify the number of images to be extracted per second as the extraction frame rate.

annotation_spec_set¶

Required. Annotation spec set resource name.

Type: str

extraction_frame_rate¶

Required. Number of frames per second to be extracted from the video.

Type: float

class google.cloud.datalabeling_v1beta1.types.ObjectDetectionMetrics(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Metrics calculated for an image object detection (bounding box) model.

pr_curve¶

Precision-recall curve.

Type: google.cloud.datalabeling_v1beta1.types.PrCurve

class google.cloud.datalabeling_v1beta1.types.ObjectTrackingConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for video object tracking human labeling task.

annotation_spec_set¶

Required. Annotation spec set resource name.

Type: str

class google.cloud.datalabeling_v1beta1.types.ObjectTrackingFrame(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video frame level annotation for object detection and tracking.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

bounding_poly¶

This field is a member of oneof bounded_area.

Type: google.cloud.datalabeling_v1beta1.types.BoundingPoly

normalized_bounding_poly¶

This field is a member of oneof bounded_area.

Type: google.cloud.datalabeling_v1beta1.types.NormalizedBoundingPoly

time_offset¶

The time offset of this frame relative to the beginning of the video.

Type: google.protobuf.duration_pb2.Duration

class google.cloud.datalabeling_v1beta1.types.OperatorMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

General information useful for labels coming from contributors.

score¶

Confidence score corresponding to a label. For examle, if 3 contributors have answered the question and 2 of them agree on the final label, the confidence score will be 0.67 (2/3).

Type: float

total_votes¶

The total number of contributors that answer this question.

Type: int

label_votes¶

The total number of contributors that choose this label.

Type: int

comments¶

Comments from contributors.

Type: MutableSequence[str]

class google.cloud.datalabeling_v1beta1.types.OutputConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

The configuration of output data.

This message has oneof fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

gcs_destination¶

Output to a file in Cloud Storage. Should be used for labeling output other than image segmentation.

This field is a member of oneof destination.

Type: google.cloud.datalabeling_v1beta1.types.GcsDestination

gcs_folder_destination¶

Output to a folder in Cloud Storage. Should be used for image segmentation labeling output.

This field is a member of oneof destination.

Type: google.cloud.datalabeling_v1beta1.types.GcsFolderDestination

class google.cloud.datalabeling_v1beta1.types.PauseEvaluationJobRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for PauseEvaluationJob.

name¶

Required. Name of the evaluation job that is going to be paused. Format:

“projects/{project_id}/evaluationJobs/{evaluation_job_id}”.

Type: str

class google.cloud.datalabeling_v1beta1.types.PdfInstruction(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Instruction from a PDF file.

gcs_file_uri¶

PDF file for the instruction. Only gcs path is allowed.

Type: str

class google.cloud.datalabeling_v1beta1.types.Polyline(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A line with multiple line segments.

vertices¶

The polyline vertices.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.Vertex]

class google.cloud.datalabeling_v1beta1.types.PolylineConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for image polyline human labeling task.

annotation_spec_set¶

Required. Annotation spec set resource name.

Type: str

instruction_message¶

Optional. Instruction message showed on contributors UI.

Type: str

class google.cloud.datalabeling_v1beta1.types.PrCurve(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

annotation_spec¶

The annotation spec of the label for which the precision-recall curve calculated. If this field is empty, that means the precision-recall curve is an aggregate curve for all labels.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

area_under_curve¶

Area under the precision-recall curve. Not to be confused with area under a receiver operating characteristic (ROC) curve.

Type: float

confidence_metrics_entries¶

Entries that make up the precision-recall graph. Each entry is a “point” on the graph drawn for a different confidence_threshold.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.PrCurve.ConfidenceMetricsEntry]

mean_average_precision¶

Mean average prcision of this curve.

Type: float

class ConfidenceMetricsEntry(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

confidence_threshold¶

Threshold used for this entry.

For classification tasks, this is a classification threshold: a predicted label is categorized as positive or negative (in the context of this point on the PR curve) based on whether the label’s score meets this threshold.

For image object detection (bounding box) tasks, this is the [intersection-over-union

(IOU)](/vision/automl/object-detection/docs/evaluate#intersection-over-union) threshold for the context of this point on the PR curve.

Type: float

recall¶

Recall value.

Type: float

precision¶

Precision value.

Type: float

f1_score¶

Harmonic mean of recall and precision.

Type: float

recall_at1¶

Recall value for entries with label that has highest score.

Type: float

precision_at1¶

Precision value for entries with label that has highest score.

Type: float

f1_score_at1¶

The harmonic mean of [recall_at1][google.cloud.datalabeling.v1beta1.PrCurve.ConfidenceMetricsEntry.recall_at1] and [precision_at1][google.cloud.datalabeling.v1beta1.PrCurve.ConfidenceMetricsEntry.precision_at1].

Type: float

recall_at5¶

Recall value for entries with label that has highest 5 scores.

Type: float

precision_at5¶

Precision value for entries with label that has highest 5 scores.

Type: float

f1_score_at5¶

The harmonic mean of [recall_at5][google.cloud.datalabeling.v1beta1.PrCurve.ConfidenceMetricsEntry.recall_at5] and [precision_at5][google.cloud.datalabeling.v1beta1.PrCurve.ConfidenceMetricsEntry.precision_at5].

Type: float

class google.cloud.datalabeling_v1beta1.types.ResumeEvaluationJobRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message ResumeEvaluationJob.

name¶

Required. Name of the evaluation job that is going to be resumed. Format:

“projects/{project_id}/evaluationJobs/{evaluation_job_id}”.

Type: str

class google.cloud.datalabeling_v1beta1.types.SearchEvaluationsRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for SearchEvaluation.

parent¶

Required. Evaluation search parent (project ID). Format: “projects/{project_id}”.

Type: str

filter¶

Optional. To search evaluations, you can filter by the following:

evaluation_job.evaluation_job_id (the last part of [EvaluationJob.name][google.cloud.datalabeling.v1beta1.EvaluationJob.name])
evaluation_job.model_id (the {model_name} portion of [EvaluationJob.modelVersion][google.cloud.datalabeling.v1beta1.EvaluationJob.model_version])
evaluation_job.evaluation_job_run_time_start (Minimum threshold for the [evaluationJobRunTime][google.cloud.datalabeling.v1beta1.Evaluation.evaluation_job_run_time] that created the evaluation)
evaluation_job.evaluation_job_run_time_end (Maximum threshold for the [evaluationJobRunTime][google.cloud.datalabeling.v1beta1.Evaluation.evaluation_job_run_time] that created the evaluation)
evaluation_job.job_state ([EvaluationJob.state][google.cloud.datalabeling.v1beta1.EvaluationJob.state])
annotation_spec.display_name (the Evaluation contains a metric for the annotation spec with this [displayName][google.cloud.datalabeling.v1beta1.AnnotationSpec.display_name])

To filter by multiple critiera, use the AND operator or the OR operator. The following examples shows a string that filters by several critiera:

“evaluationjob.evaluation_job_id = {evaluation_job_id} AND evaluationjob.model_id = {model_name} AND evaluationjob.evaluation_job_run_time_start = {timestamp_1} AND evaluationjob.evaluation_job_run_time_end = {timestamp_2} AND annotation_spec.display_name = {display_name}”.

Type: str

page_size¶

Optional. Requested page size. Server may return fewer results than requested. Default value is 100.

Type: int

page_token¶

Optional. A token identifying a page of results for the server to return. Typically obtained by the [nextPageToken][google.cloud.datalabeling.v1beta1.SearchEvaluationsResponse.next_page_token] of the response to a previous search request.

If you don’t specify this field, the API call requests the first page of the search.

Type: str

class google.cloud.datalabeling_v1beta1.types.SearchEvaluationsResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Results of searching evaluations.

evaluations¶

The list of evaluations matching the search.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.Evaluation]

next_page_token¶

A token to retrieve next page of results.

Type: str

class google.cloud.datalabeling_v1beta1.types.SearchExampleComparisonsRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message of SearchExampleComparisons.

parent¶

Required. Name of the [Evaluation][google.cloud.datalabeling.v1beta1.Evaluation] resource to search for example comparisons from. Format:

“projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}”.

Type: str

page_size¶

Optional. Requested page size. Server may return fewer results than requested. Default value is 100.

Type: int

page_token¶

Optional. A token identifying a page of results for the server to return. Typically obtained by the [nextPageToken][SearchExampleComparisons.next_page_token] of the response to a previous search rquest.

If you don’t specify this field, the API call requests the first page of the search.

Type: str

class google.cloud.datalabeling_v1beta1.types.SearchExampleComparisonsResponse(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Results of searching example comparisons.

example_comparisons¶

A list of example comparisons matching the search criteria.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.SearchExampleComparisonsResponse.ExampleComparison]

next_page_token¶

A token to retrieve next page of results.

Type: str

class ExampleComparison(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Example comparisons comparing ground truth output and predictions for a specific input.

ground_truth_example¶

The ground truth output for the input.

Type: google.cloud.datalabeling_v1beta1.types.Example

model_created_examples¶

Predictions by the model for the input.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.Example]

class google.cloud.datalabeling_v1beta1.types.SegmentationConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for image segmentation

annotation_spec_set¶

Required. Annotation spec set resource name. format: projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}

Type: str

instruction_message¶

Instruction message showed on labelers UI.

Type: str

class google.cloud.datalabeling_v1beta1.types.SentimentConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for setting up sentiments.

enable_label_sentiment_selection¶

If set to true, contributors will have the option to select sentiment of the label they selected, to mark it as negative or positive label. Default is false.

Type: bool

class google.cloud.datalabeling_v1beta1.types.SequentialSegment(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Start and end position in a sequence (e.g. text segment).

start¶

Start position (inclusive).

Type: int

end¶

End position (exclusive).

Type: int

class google.cloud.datalabeling_v1beta1.types.StringAggregationType(value)[source]¶

Bases: proto.enums.Enum

Values:

STRING_AGGREGATION_TYPE_UNSPECIFIED (0):: No description available.
MAJORITY_VOTE (1):: Majority vote to aggregate answers.
UNANIMOUS_VOTE (2):: Unanimous answers will be adopted.
NO_AGGREGATION (3):: Preserve all answers by crowd compute.

class google.cloud.datalabeling_v1beta1.types.TextClassificationAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Text classification annotation.

annotation_spec¶

Label of the text.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

class google.cloud.datalabeling_v1beta1.types.TextClassificationConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for text classification human labeling task.

allow_multi_label¶

Optional. If allow_multi_label is true, contributors are able to choose multiple labels for one text segment.

Type: bool

annotation_spec_set¶

Required. Annotation spec set resource name.

Type: str

sentiment_config¶

Optional. Configs for sentiment selection.

Type: google.cloud.datalabeling_v1beta1.types.SentimentConfig

class google.cloud.datalabeling_v1beta1.types.TextEntityExtractionAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Text entity extraction annotation.

annotation_spec¶

Label of the text entities.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

sequential_segment¶

Position of the entity.

Type: google.cloud.datalabeling_v1beta1.types.SequentialSegment

class google.cloud.datalabeling_v1beta1.types.TextEntityExtractionConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for text entity extraction human labeling task.

annotation_spec_set¶

Required. Annotation spec set resource name.

Type: str

class google.cloud.datalabeling_v1beta1.types.TextMetadata(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Metadata for the text.

language_code¶

The language of this text, as a BCP-47. Default value is en-US.

Type: str

class google.cloud.datalabeling_v1beta1.types.TextPayload(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Container of information about a piece of text.

text_content¶

Text content.

Type: str

class google.cloud.datalabeling_v1beta1.types.TimeSegment(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A time period inside of an example that has a time dimension (e.g. video).

start_time_offset¶

Start of the time segment (inclusive), represented as the duration since the example start.

Type: google.protobuf.duration_pb2.Duration

end_time_offset¶

End of the time segment (exclusive), represented as the duration since the example start.

Type: google.protobuf.duration_pb2.Duration

class google.cloud.datalabeling_v1beta1.types.UpdateEvaluationJobRequest(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Request message for UpdateEvaluationJob.

evaluation_job¶

Required. Evaluation job that is going to be updated.

Type: google.cloud.datalabeling_v1beta1.types.EvaluationJob

update_mask¶

Optional. Mask for which fields to update. You can only provide the following fields:

evaluationJobConfig.humanAnnotationConfig.instruction
evaluationJobConfig.exampleCount
evaluationJobConfig.exampleSamplePercentage

You can provide more than one of these fields by separating them with commas.

Type: google.protobuf.field_mask_pb2.FieldMask

class google.cloud.datalabeling_v1beta1.types.Vertex(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

A vertex represents a 2D point in the image. NOTE: the vertex coordinates are in the same scale as the original image.

x¶

X coordinate.

Type: int

y¶

Y coordinate.

Type: int

class google.cloud.datalabeling_v1beta1.types.VideoClassificationAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video classification annotation.

time_segment¶

The time segment of the video to which the annotation applies.

Type: google.cloud.datalabeling_v1beta1.types.TimeSegment

annotation_spec¶

Label of the segment specified by time_segment.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

class google.cloud.datalabeling_v1beta1.types.VideoClassificationConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Config for video classification human labeling task. Currently two types of video classification are supported:

Assign labels on the entire video.
Split the video into multiple video clips based on camera
shot, and assign labels on each video clip.

annotation_spec_set_configs¶

Required. The list of annotation spec set configs. Since watching a video clip takes much longer time than an image, we support label with multiple AnnotationSpecSet at the same time. Labels in each AnnotationSpecSet will be shown in a group to contributors. Contributors can select one or more (depending on whether to allow multi label) from each group.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.VideoClassificationConfig.AnnotationSpecSetConfig]

apply_shot_detection¶

Optional. Option to apply shot detection on the video.

Type: bool

class AnnotationSpecSetConfig(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Annotation spec set with the setting of allowing multi labels or not.

annotation_spec_set¶

Required. Annotation spec set resource name.

Type: str

allow_multi_label¶

Optional. If allow_multi_label is true, contributors are able to choose multiple labels from one annotation spec set.

Type: bool

class google.cloud.datalabeling_v1beta1.types.VideoEventAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video event annotation.

annotation_spec¶

Label of the event in this annotation.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

time_segment¶

The time segment of the video to which the annotation applies.

Type: google.cloud.datalabeling_v1beta1.types.TimeSegment

class google.cloud.datalabeling_v1beta1.types.VideoObjectTrackingAnnotation(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Video object tracking annotation.

annotation_spec¶

Label of the object tracked in this annotation.

Type: google.cloud.datalabeling_v1beta1.types.AnnotationSpec

time_segment¶

The time segment of the video to which object tracking applies.

Type: google.cloud.datalabeling_v1beta1.types.TimeSegment

object_tracking_frames¶

The list of frames where this object track appears.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.ObjectTrackingFrame]

class google.cloud.datalabeling_v1beta1.types.VideoPayload(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Container of information of a video.

mime_type¶

Video format.

Type: str

video_uri¶

Video uri from the user bucket.

Type: str

video_thumbnails¶

The list of video thumbnails.

Type: MutableSequence[google.cloud.datalabeling_v1beta1.types.VideoThumbnail]

frame_rate¶

FPS of the video.

Type: float

signed_uri¶

Signed uri of the video file in the service bucket.

Type: str

class google.cloud.datalabeling_v1beta1.types.VideoThumbnail(mapping=None, *, ignore_unknown_fields=False, **kwargs)[source]¶

Bases: proto.message.Message

Container of information of a video thumbnail.

thumbnail¶

A byte string of the video frame.

Type: bytes

time_offset¶

Time offset relative to the beginning of the video, corresponding to the video frame where the thumbnail has been extracted from.

Type: google.protobuf.duration_pb2.Duration

Types for Google Cloud Datalabeling v1beta1 API¶

google-cloud-datalabeling

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